Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
With an explosive growth of blogs, information seeking in blogosphere becomes more and more challenging. One example task is to find the most relevant topical blogs against a give...
— Many open source software (OSS) development projects use tools and models that come from heterogeneous sources. A project manager, who wants to analyze indicators for the state...
Word prediction performed by language models has an important role in many tasks as e.g. word sense disambiguation, speech recognition, hand-writing recognition, query spelling an...